The Resource Parking Availability Forecasting Model, by Manohar Boorlu
Parking Availability Forecasting Model, by Manohar Boorlu
Resource Information
The item Parking Availability Forecasting Model, by Manohar Boorlu represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries.This item is available to borrow from all library branches.
Resource Information
The item Parking Availability Forecasting Model, by Manohar Boorlu represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri-Kansas City Libraries.
This item is available to borrow from all library branches.
- Summary
- Parking is increasingly an issue in the world today especially in large and growing cities with contemporary urban mobility. The effort spent in searching for available parking spots results in significant loss of resources such as time, and fuel, as well as environmental pollution. Parking Availability can be influenced by many factors such as time of day, day of week, location, nearby events, weather and traffic conditions. Driven by the idea of predicting parking availability to help drivers plan ahead of time, we contribute a Parking Availability Forecasting Model, which uses a time series analysis and machine-learning algorithms to predict the number of available parking spots at a certain location on a desired date and time. The forecasting model is trained on historical parking data from the cities of Kansas City, US and Melbourne, Australia. This paper also compares the accuracy of different time-series forecasting models, and how each of them fits our use-case scenario. Multivariate data analysis together with temperature and weather summary are used to cross-validate our forecasting model
- Language
- eng
- Extent
- 1 online resource (26 pages)
- Note
-
- "A thesis in Computer Science."
- Advisor: Mohammad Amin Kuhail
- Vita
- Contents
-
- Introduction
- Background and related work
- Dataset
- Parking availability forecasting model
- Implementation and results
- Conclusion and future work
- Label
- Parking Availability Forecasting Model
- Title
- Parking Availability Forecasting Model
- Statement of responsibility
- by Manohar Boorlu
- Language
- eng
- Summary
- Parking is increasingly an issue in the world today especially in large and growing cities with contemporary urban mobility. The effort spent in searching for available parking spots results in significant loss of resources such as time, and fuel, as well as environmental pollution. Parking Availability can be influenced by many factors such as time of day, day of week, location, nearby events, weather and traffic conditions. Driven by the idea of predicting parking availability to help drivers plan ahead of time, we contribute a Parking Availability Forecasting Model, which uses a time series analysis and machine-learning algorithms to predict the number of available parking spots at a certain location on a desired date and time. The forecasting model is trained on historical parking data from the cities of Kansas City, US and Melbourne, Australia. This paper also compares the accuracy of different time-series forecasting models, and how each of them fits our use-case scenario. Multivariate data analysis together with temperature and weather summary are used to cross-validate our forecasting model
- Cataloging source
- UMK
- http://library.link/vocab/creatorName
- Boorlu, Manohar
- Degree
- M.S.
- Dissertation note
- (School of Computing and Engineering).
- Dissertation year
- 2019.
- Granting institution
- University of Missouri-Kansas City,
- Illustrations
-
- illustrations
- maps
- Index
- no index present
- Literary form
- non fiction
- Nature of contents
-
- dictionaries
- bibliography
- theses
- http://library.link/vocab/relatedWorkOrContributorName
- Kuhail, Mohammad Amin
- http://library.link/vocab/subjectName
-
- Automobile parking
- Automobile parking
- Label
- Parking Availability Forecasting Model, by Manohar Boorlu
- Note
-
- "A thesis in Computer Science."
- Advisor: Mohammad Amin Kuhail
- Vita
- Antecedent source
- not applicable
- Bibliography note
- Includes bibliographical references (pages 22-25)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- black and white
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Background and related work -- Dataset -- Parking availability forecasting model -- Implementation and results -- Conclusion and future work
- Control code
- 1121203399
- Dimensions
- unknown
- Extent
- 1 online resource (26 pages)
- File format
- one file format
- Form of item
- online
- Level of compression
- mixed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations, maps
- Quality assurance targets
- not applicable
- Specific material designation
- remote
- System control number
- (OCoLC)1121203399
- System details
-
- The full text of the thesis is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
- Mode of access: World Wide Web
- Label
- Parking Availability Forecasting Model, by Manohar Boorlu
- Note
-
- "A thesis in Computer Science."
- Advisor: Mohammad Amin Kuhail
- Vita
- Antecedent source
- not applicable
- Bibliography note
- Includes bibliographical references (pages 22-25)
- Carrier category
- online resource
- Carrier category code
-
- cr
- Carrier MARC source
- rdacarrier
- Color
- black and white
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- Background and related work -- Dataset -- Parking availability forecasting model -- Implementation and results -- Conclusion and future work
- Control code
- 1121203399
- Dimensions
- unknown
- Extent
- 1 online resource (26 pages)
- File format
- one file format
- Form of item
- online
- Level of compression
- mixed
- Media category
- computer
- Media MARC source
- rdamedia
- Media type code
-
- c
- Other physical details
- illustrations, maps
- Quality assurance targets
- not applicable
- Specific material designation
- remote
- System control number
- (OCoLC)1121203399
- System details
-
- The full text of the thesis is available as an Adobe Acrobat .pdf file; Adobe Acrobat Reader required to view the file
- Mode of access: World Wide Web
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.umkc.edu/portal/Parking-Availability-Forecasting-Model-by/yYxyK_Slzk8/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.umkc.edu/portal/Parking-Availability-Forecasting-Model-by/yYxyK_Slzk8/">Parking Availability Forecasting Model, by Manohar Boorlu</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.umkc.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.umkc.edu/">University of Missouri-Kansas City Libraries</a></span></span></span></span></div>
